• Course overview
  • Course details
  • Prerequisites

Course overview

About this course

This course This intermediate-level course prepares you for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam by providing a comprehensive exploration of the exam topics. You'll delve into the key areas covered on the exam, understanding how they relate to developing AI and machine learning solutions on the AWS platform. Through detailed explanations and walkthroughs of exam style questions, you'll reinforce your knowledge, identify gaps in your understanding, and gain valuable
strategies for tackling questions effectively. The course includes review of exam-style sample questions, to help you recognize incorrect responses and hone your test-taking abilities. By the end, you'll have a firm grasp on the concepts and practical applications tested on the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam.

Audience profile 

This course is intended for individuals who are preparing for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam.

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Course details

Domain 1: Data Preparation for Machine Learning (ML)
1.1 Ingest and store data.
1.2 Transform data and perform feature engineering.
1.3 Ensure data integrity and prepare data for modeling.

Domain 2: ML Model Development
2.1 Choose a modeling approach.
2.2 Train and refine models.
2.3 Analyze model performance.

Domain 3: Deployment and Orchestration of ML Workflows
3.1 Select deployment infrastructure based on existing architecture and requirements.
3.2 Create and script infrastructure based on existing architecture and requirements.
3.3 Use automated orchestration tools to set up continuous integration and continuous delivery (CI/CD) pipelines.

Domain 4: ML Solution Monitoring, Maintenance, and Security
4.1 Monitor model interference.
4.2 Monitor and optimize infrastructure costs.
4.3 Secure AWS resources.

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Prerequisites

  • General IT knowledge
  • Basic AWS knowledge

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